In the electrical power generation and distribution industry, monitoring transmission and distribution networks for fault conditions is very important. The term distribution network is used herein to refer to any electrical power transmission or distribution facility. Moreover, a fault condition is any abnormal (unexpected) current-conducting path in a distribution network. Fault conditions often present danger to people and property. They also waste electrical energy.
One type of fault is a bolted (short-circuit) fault of one or more legs of a distribution network to another leg thereof or to ground. This type of low-impedance (low-Z) fault condition is easily detected by conventional circuit overcurrent protective devices such as fuses or circuit breakers. In other words, a complete short circuit (a low-impedance path) usually trips a circuit breaker or blows a fuse. A circuit of the distribution network experiencing such a fault condition is quickly removed from service until such time as repairs can be effected (i.e., until the fault is cleared).
Another type of fault condition occurs when an unintended high impedance (high-Z) conductive path occurs between transmission line legs or between one leg and ground. Such high-Z paths may occur when a tree limb or the like falls across a transmission line or when a single leg of a transmission line breaks (due to ice or wind, for example) and touches the ground. Generally, a single conductor of the distribution network dropping to the ground will not create a short circuit, but will continue to allow current flow at a relatively low rate. Such current flow often causes arcing. This condition presents a great danger of electrocution to people or animals happening across the downed conductor. The arcing can also result in fires.
A problem constantly plaguing the electrical power industry is finding an effective way to differentiate between a high-Z fault (HIF) condition and similar effects caused by changes in the loads attached to the distribution network. In addition to load switching events, power factor correcting capacitor banks are frequently switched on and off the network and transformer taps are automatically changed to keep the network voltage constant. Both of these events also create conditions on the network which may appear similar to an HIF condition. Any effective system for detecting HIFs must be able to distinguish fault conditions from normal load switching events. A system which ignores legitimate HIF conditions risks the aforementioned dangers while a system which falsely trips in response to normal load switching events can wrack havoc with consumers relying on uninterrupted electrical service. Interruption of electrical service to certain manufacturing processes, for example, may destroy work-in-process and result in large expense to the manufacturer. An interruption of medical apparatus can also be inconvenient at best, and disastrous at worst.
HIF detection solutions as simple as lowering the trip points of conventional circuit protective devices have been tried. Because HIF-drawn current is often a very small percentage of the total network current, this solution has done nothing more than cause excessive service interruptions. Most HIF research has focused upon the problem of finding detectable differences in measurable parameters in a distribution network under HIF and normal load switching conditions. Some of the parameters measured and compared have included phase current, ground current, ratio of ground current to positive sequence current, and frequency spectra--both near line frequency (typically 60 Hz.) and at higher harmonic relationships to line frequency.
One system with potential for detecting HIFs is disclosed in U.S. Pat. No. 5,223,795 issued to Frederick K. Blades, titled "Method and Apparatus for Detecting Arcing in Electrical Connections by Monitoring High Frequency Noise". Blades discloses a system wherein high-frequency noise caused by arcing is detected and, when measured above a pre-programmed threshold level, trips a circuit protective device. While the Blades system is intended for residential branch circuit uses, it is representative of a class of HIF detection strategies relying on high-frequency noise for use in power distribution networks. These techniques have not proven effective in the detection of HIFs, since noise generated by HIFs varies widely in both spectrum and intensity. In addition, capacitor banks, automatically switched on and off the network for power factor correction, tend to short the high-frequency noise signals to ground, adding additional uncertainty to the detection and analysis process.
Another approach to HIF detection is taught in U.S. Pat. No. 5,216,621 issued to Richard T. Dickens, titled "Line Disturbance-Monitor and Recorder System". Dickens discloses a system comprising analog current and/or voltage sensors placed at selected positions in a distribution network. Analog signals from the detectors are digitized by analog-to-digital (A/D) converters and presented to a high-speed digital signal processor (DSP) as digital sample words. The DSP computes both the real and imaginary phasor components of the operating parameter or parameters. These phasor components are then used to calculate various measures of power transmission performance according to known phasor equations. Trigger means implemented within the DSP provides an output signal when pre-programmed limits of a measured or calculated quantity are exceeded. Memory in cooperation with the DSP captures and stores digital sample words associated with abnormal events for future analysis. The Dickens apparatus appears to be expensive to build and, even with a state-of-the-art DSP, the system may only detect HIFs with well-known characteristics. Each installation on a network may have to be individually calibrated to the characteristics of that network and, as the loads changed on the network (e.g., by adding or removing power customers), the system would have to be re-calibrated.
A third approach to HIF detection is disclosed in U.S. Pat. No. 4,878,142 issued to Sten Bergman, et al., titled "High Resistance Ground Fault Protection". Bergman discloses a system for analyzing the non-harmonic components of phase currents. A estimate of Fourier coefficients is computed, thereby transforming the time-domain information into the frequency domain. Both the original digitized signals and the transformed frequency domain signals are applied to detection circuitry. Logical decisions based on comparison to known fault parameters are made and a fault-indicating trip signal is provided when appropriate. The Bergman system suffers from many of the same shortcomings as the aforementioned Dickens system. The Bergman system must be calibrated to each network and re-calibrated when the load profile on the network changes.
Yet a fourth HIF detection system is described in "A Neural Network Approach to the Detection of Incipient Faults on Power Distribution Feeders", paper No. 89 TD 377-3 PWRD, S. Ebron, D. Lubkemen and M. White (1989). That HIF detection system relies on the monitoring, digitization, and comparison of voltage and current conditions in the distribution network. The mechanism for deciding whether an event is an HIF or a normal load switching event is a partially or fully-trained neural network. The 200-node neural network described by Ebron et al. is trained using data obtained from a computer-simulated distribution network using the Electromagnetic Transients Program (EMTP) by Systems Control, Inc. Data is collected for ten cycles (two subsequent zero-crossings going from negative to positive) of simulated operation. Digitized data is pre-processed to extract features such as peak transient current over three phases, and phase currents immediately before and after the occurrence of a detected transient. The extracted feature vector representing ten cycles of simulated network operation is then applied to a neural network. The network, once at least partially trained, then identifies patterns in the data as either HIF or normal load switch events. A trigger signal can be generated when an HIF is detected.
It is therefore an object of the present invention is to provide a method and apparatus for monitoring an electrical power distribution network and for distinguishing HIF conditions from normal load, capacitor bank or transformer tap switching conditions with extremely high accuracy.
It is a further object of the invention to produce a system self-adaptable to a variety of networks and one that need not be calibrated for changes in load on the network.
It is still a further object of the invention to provide a self-contained, low-cost, single-chip hardware implementation of the inventive method for use either as a standalone HIF monitor, or as an integral part of a circuit-interrupting device for completely self-contained fault clearing.